Updating Autonomous Underwater Vehicle Risk Based on the Effectiveness of Failure Prevention and Correction

Updating Autonomous Underwater Vehicle Risk Based on the Effectiveness of Failure Prevention and... AbstractAutonomous underwater vehicles (AUVs) have proven to be feasible platforms for marine observations. Risk and reliability studies on the performance of these vehicles by different groups show a significant difference in reliability, with the observation that the outcomes depend on whether the vehicles are operated by developers or nondevelopers. This paper shows that this difference in reliability is due to the failure prevention and correction procedures—risk mitigation—put in place by developers. However, no formalization has been developed for updating the risk profile based on the expected effectiveness of the failure prevention and correction process. A generic Bayesian approach for updating the risk profile is presented, based on the probability of failure prevention and correction and the number of subsequent deployments on which the failure does not occur. The approach, which applies whether the risk profile is captured in a parametric or nonparametric survival model, is applied to a real case study of the International Submarine Engineering Ltd. (ISE) Explorer AUV. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

Updating Autonomous Underwater Vehicle Risk Based on the Effectiveness of Failure Prevention and Correction

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0426
eISSN
1520-0426
D.O.I.
10.1175/JTECH-D-16-0252.1
Publisher site
See Article on Publisher Site

Abstract

AbstractAutonomous underwater vehicles (AUVs) have proven to be feasible platforms for marine observations. Risk and reliability studies on the performance of these vehicles by different groups show a significant difference in reliability, with the observation that the outcomes depend on whether the vehicles are operated by developers or nondevelopers. This paper shows that this difference in reliability is due to the failure prevention and correction procedures—risk mitigation—put in place by developers. However, no formalization has been developed for updating the risk profile based on the expected effectiveness of the failure prevention and correction process. A generic Bayesian approach for updating the risk profile is presented, based on the probability of failure prevention and correction and the number of subsequent deployments on which the failure does not occur. The approach, which applies whether the risk profile is captured in a parametric or nonparametric survival model, is applied to a real case study of the International Submarine Engineering Ltd. (ISE) Explorer AUV.

Journal

Journal of Atmospheric and Oceanic TechnologyAmerican Meteorological Society

Published: Apr 27, 2018

References

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